It is time to announce the participants for in the STE||AR Group’s 2020 Google Summer of Code! We are very proud to announce the names of those 5 students this year who will be funded by Google to work on projects for our group.
These recipients represent only a handful of the many excellent proposals that we had to choose from. For those unfamiliar with the program, the Google Summer of Code brings together ambitious students from around the world with open source developers by giving each mentoring organization funds to hire a set number of participants. Students then write proposals, which they submit to a mentoring organization, in hopes of having their work funded.
Below are the students who will be working with the STE||AR Group this summer listed with their mentors and their proposal abstracts.
Participant:
Sayef Azad Sakin, University of Arizona
Mentor:
Kate Isaacs, University of Arizona
Project: Time Series Updates for Traveler
Traveler-Integrated is a platform for performance visualization of parallel runtimes such as HPX. The interface allows accessing multiple datasets, from different executions. However, there are several improvements that can be made to the interface in terms of managing large numbers of files (e.g., from historical regression runs) and organizing windows to handle comparison of runs. In this project you will work on the Javascript front end to implement this interface, refining the design through user feedback.
Participant:
Giannis Gonidelis, TS Aristotle University of Thessaloniki
Mentor:
Hartmut Kaiser, Louisiana State University
Thomas Heller, Exasol
Project: Adapt HPX range-based parallel algorithms in order to expose a range based interface according to latest Ranges
Our parallel algorithms currently expect for the begin iterators to have the same type as the corresponding end iterators. The latest changes to the C++ Standard allow for those to be different. This enables the use of the algorithms with more general range abstractions (i.e. begin-iterator/sentinel pairs such as C-style strings). We have created a list of algorithms that need to be changed to support different types for the begin/end iterator pairs (see here). There you can also see what algorithms have already been adapted, which may help in understanding the task.
Participant:
Pranav Gadikar, Indian Institute of Technology Madras
Mentor:
Patrick Diehl, Louisiana State Univesrity
Prashant J Kumar, UT Austin
Project: Domain decomposition, load balancing, and massively parallel solvers for the class of nonlocal models
Peridynamics is used to model cracks and fractures in materials. In recent years there have been several numerical approximations proposed for peridynamics. Peridynamics is a nonlocal model, i.e. to compute force/strain/energy at a point, one has to look at the neighbors of a point within a finite radius. A code utilizing the parallel algorithms and futurization within HPX for a single shared memory node is available. This code should be extended with a domain decomposition for computations on several nodes. Here, the challenge would be to perform an efficient load balancing of the domain partitions. In case of damage, the computational costs in the domain where the damage occurs in the material decreases. In this project, an efficient algorithm which detects where the computational costs are decreasing and how to redistribute the domains such that load is balanced should be developed.
Participant:
Weile Wei, Louisiana State University
Mentor:
John Biddiscombe, Swiss National Supercomputing Center
Mikael Simberg, Swiss National Supercomputing Center
Project: Concurrent Data structure Support
STL containers such as vectors/maps/sets/etc are not thread safe. One cannot safely add or remove elements from one of these containers in one thread, whilst iterating or adding/removing in another thread without potentially catastrophic consequences (usually segmentation faults leading to eventual program failure). Some work has begun on implementing concurrent structures in HPX, a concurrent unordered map with reader/writer lock and a partial implementation of concurrent vector exist, but they have not all been completed, do not have unit tests and need to be unified into an hpx::concurrent namespace. A number of libraries implementing thread safe (sometimes lockfree) containers already exist that can be used for ideas and where code uses a boost compatible license can be integrated into HPX. The aim of the project is to collect as much information and as many implementations of threads safe containers and create or integrate them into the HPX library.
Participant:
Mahesh Kale, Indian Institute of Technology Roorke
Mentor:
Nikunj Gupta, Indian Institute of Technology Roorke
Parsa Amini, Louisiana State University
Project: Pip Package for Phylanx
Phylanx relies on many external libraries which makes the building process tedious and error prone, especially to the target audience of the software- domain scientist. The goal of this project is to automate the build process of Phylanx by creating a distribution package. The distribution package should build and install Phylanx and its requirements through Python’s pip package manager.